1. Field of the Invention
The present invention generally relates to data processing systems, and more particularly relates to such systems that analyze survey data.
2. Description of the Prior Art
Many businesses have adopted the concept of Total Quality Management (TQM) to help improve profitability, ensure sustained customer loyalty, improve quality of products, etc. Originally developed by E. Deming and others, TQM is now widely accepted in many business circles throughout the world. A cornerstone of most total quality management (TQM) systems is the periodic measurement of identified parameters that relate to various aspects of the business. Through these measurements, managers can identify the areas within the organization that need improvement. Because the measurements are made on a “periodic” basis, managers can gauge the effects of various changes made within the organization over time. The goal of most TQM systems is to make continuous improvement within the organization.
Businesses often generate and manage an array of measurements for purposes of analyzing the performance of individual operations in relationship to productivity, resource utilization, profitability, etc. One of the most important measurements in many TQM systems is that of customer satisfaction. To measure customer satisfaction, periodic customer feedback is required, usually obtained through customer surveys.
In many surveys, customers are asked a number of survey questions that are related to various products and/or services provided by a business. For many questions, the customers can respond both with a satisfaction rating and an importance rating. By analyzing the answers to these questions, managers can obtain insights into many areas, including customer loyalty, overall satisfaction, potential weakness, etc.
It is not uncommon for businesses to conduct their own customer surveys. However, it is increasingly popular to outsource this function to outside vendors who specialize in conducting customer surveys. Today, there are a number of vendors who conduct customer surveys, and provide a survey database to the subscribing business. One such company is Prognostics Inc., located in Menlo Park, Calif. An advantage of using such a vendor is that customer survey data for other companies, including competing companies, can often be obtained. This enables a business to perform comparisons between itself and its competitors.
Some of the vendors of customer surveys provide the survey data in electronic form, and often provide a software program for accessing the survey database. The software programs facilitate the generation of reports or the like, which can then be used by management. Prognostics is one such vendor. Prognostics provides survey data in a proprietary electronic format, and provides a software program called the Research Analysis Program (RAP) which can access the survey data. RAP can read the survey database, perform data requests, and provide a number of reports.
A limitation of many of the survey analysis programs is that the survey results may mislead the user. For example, survey results may be based on a statistically insignificant sample size, thereby misleading the user. Similarly, survey results may be based on data elements that skew the results in an undesirable way. Often, the user is unaware that the survey results have these deficiencies, and may base important business decisions on the misrepresentative survey results.
Misrepresentative results can often be traced to portions of the survey database that are either under-represented, or otherwise different from the user's expectations. The underlying assumption when using a typical survey analysis program is that the survey database is fully represented in all respects, and that all data elements fall within the user's expectations. It has been found that this is often not the case.
For example, it is known that many survey analysis programs allow the user to make qualified user requests that select and operate only on a portion of the database. Using such a qualified request, a user may request the overall satisfaction for those respondents that are in a particular industry sector, that are located in a particular geographic region, and that use a particular product. The number of respondents represented in the survey database that meet all of these criteria may be relatively small. Thus, in this case, the corresponding results may be based on a statistically insignificant sample size. The user may not recognize this, and may make important business decisions based upon the misrepresentative results.
In another example, the survey database may include data elements that skew the results in an undesirable way. For example, it is known that many questions in a customer survey may solicit two answers, such as an overall importance question and an overall satisfaction question. Those responses that indicate a high degree of satisfaction but a low degree of importance may skew the results provided by an overall satisfaction request. In addition, some respondents may only answer one of the two questions, such as the satisfaction question but not the importance question. This may also skew the results of certain user requests.